Computational fluid dynamics has become an extremely successful framework to understand a range of natural phenomena ranging from astrophysics to everyday technological applications. Despite these successes, it is increasingly realized that many phenomena in plasma physics require a kinetic description [1]}, [2]}. The most challenging aspect of kinetic models, from a computational point of view, is certainly the up to six-dimensional phase space. The traditional approach to overcome this difficulty has been to employ so-called particle methods [3]}, [4]}. While these simulations are comparably cheap and have been successfully employed in some applications, it is well known that they miss or do not resolve accurately certain physical phenomena, such as Landau damping. In addition, the inherent numerical noise introduced makes it extremely difficult to obtain accurate results for many physical phenomena. More recently, sparse grids [5]}, [6]} and low-rank methods [7]}, [8]} have been used to reduce memory requirements and computational complexity. Nevertheless, the need to run fully kinetic simulations in high dimension persists for a range of applications.
